move all aws param definitions as gitlab env variables

[chouetz]

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What does this PR do?

Centralize aws ssm parameters to easily list and document them Relates to #23529

Motivation

incident-25366 In case of secret disclosure we can check params easily

Additional Notes

Possible Drawbacks / Trade-offs

Describe how to test/QA your changes

[pr-commenter[bot]]

Bloop Bleep... Dogbot Here

Regression Detector Results

Run ID: 9521ff0a-0195-4ac9-a47e-4a5ad7ba7e09 Baseline: d6a7e7927b96c58b1ca37d5a45453a1a457e3958 Comparison: 9816fb7f80b447073a626d9f69dca2aeadc8d95a

Performance changes are noted in the perf column of each table:

• ✅ = significantly better comparison variant performance
• ❌ = significantly worse comparison variant performance
• ➖ = no significant change in performance

No significant changes in experiment optimization goals

Confidence level: 90.00% Effect size tolerance: |Δ mean %| ≥ 5.00%

There were no significant changes in experiment optimization goals at this confidence level and effect size tolerance.

Experiments ignored for regressions

Regressions in experiments with settings containing erratic: true are ignored.

perf	experiment	goal	Δ mean %	Δ mean % CI
➖	file_to_blackhole	% cpu utilization	-0.27	[-6.83, +6.29]

Fine details of change detection per experiment

perf	experiment	goal	Δ mean %	Δ mean % CI
➖	otel_to_otel_logs	ingress throughput	+0.72	[+0.08, +1.36]
➖	process_agent_real_time_mode	memory utilization	+0.54	[+0.50, +0.59]
➖	idle	memory utilization	+0.30	[+0.26, +0.34]
➖	basic_py_check	% cpu utilization	+0.27	[-1.94, +2.48]
➖	file_tree	memory utilization	+0.04	[-0.04, +0.12]
➖	trace_agent_msgpack	ingress throughput	+0.02	[+0.01, +0.03]
➖	trace_agent_json	ingress throughput	+0.00	[-0.03, +0.04]
➖	tcp_dd_logs_filter_exclude	ingress throughput	+0.00	[-0.00, +0.00]
➖	uds_dogstatsd_to_api	ingress throughput	-0.00	[-0.00, +0.00]
➖	uds_dogstatsd_to_api_cpu	% cpu utilization	-0.05	[-1.49, +1.39]
➖	process_agent_standard_check_with_stats	memory utilization	-0.07	[-0.10, -0.05]
➖	tcp_syslog_to_blackhole	ingress throughput	-0.17	[-0.22, -0.12]
➖	file_to_blackhole	% cpu utilization	-0.27	[-6.83, +6.29]
➖	process_agent_standard_check	memory utilization	-0.34	[-0.38, -0.29]

Explanation

A regression test is an A/B test of target performance in a repeatable rig, where "performance" is measured as "comparison variant minus baseline variant" for an optimization goal (e.g., ingress throughput). Due to intrinsic variability in measuring that goal, we can only estimate its mean value for each experiment; we report uncertainty in that value as a 90.00% confidence interval denoted "Δ mean % CI".

For each experiment, we decide whether a change in performance is a "regression" -- a change worth investigating further -- if all of the following criteria are true:

1. Its estimated |Δ mean %| ≥ 5.00%, indicating the change is big enough to merit a closer look.

2. Its 90.00% confidence interval "Δ mean % CI" does not contain zero, indicating that if our statistical model is accurate, there is at least a 90.00% chance there is a difference in performance between baseline and comparison variants.

3. Its configuration does not mark it "erratic".

[chouetz]

/trigger-ci --variable RUN_ALL_BUILDS=true --variable RUN_KITCHEN_TESTS=true --variable RUN_E2E_TESTS=on --variable DEPLOY_AGENT=true --variable RUN_UNIT_TESTS=on

[dd-devflow[bot]]

:steam_locomotive: Gitlab pipeline started

Started pipeline #30103753

[pr-commenter[bot]]

Test changes on VM

Use this command from test-infra-definitions to manually test this PR changes on a VM:

inv create-vm --pipeline-id=30103753 --os-family=ubuntu

[pr-commenter[bot]]

Regression Detector

Regression Detector Results

Run ID: 79a6a526-93c0-4142-a742-60730e5d5173 Baseline: b2368e32b25fa184028187e130095a2fd7bed6e6 Comparison: 2dcc0a16b5a33508801a84b21604167df6f38600

Performance changes are noted in the perf column of each table:

• ✅ = significantly better comparison variant performance
• ❌ = significantly worse comparison variant performance
• ➖ = no significant change in performance

No significant changes in experiment optimization goals

Confidence level: 90.00% Effect size tolerance: |Δ mean %| ≥ 5.00%

There were no significant changes in experiment optimization goals at this confidence level and effect size tolerance.

Experiments ignored for regressions

Regressions in experiments with settings containing erratic: true are ignored.

perf	experiment	goal	Δ mean %	Δ mean % CI
➖	file_to_blackhole	% cpu utilization	-3.29	[-10.05, +3.47]

Fine details of change detection per experiment

perf	experiment	goal	Δ mean %	Δ mean % CI
➖	pycheck_1000_100byte_tags	% cpu utilization	+0.62	[-4.56, +5.80]
➖	uds_dogstatsd_to_api_cpu	% cpu utilization	+0.25	[-2.61, +3.12]
➖	file_tree	memory utilization	+0.20	[+0.09, +0.31]
➖	basic_py_check	% cpu utilization	+0.07	[-2.24, +2.38]
➖	uds_dogstatsd_to_api	ingress throughput	+0.02	[-0.19, +0.22]
➖	tcp_dd_logs_filter_exclude	ingress throughput	+0.00	[-0.00, +0.00]
➖	trace_agent_json	ingress throughput	-0.01	[-0.04, +0.03]
➖	trace_agent_msgpack	ingress throughput	-0.02	[-0.03, -0.01]
➖	process_agent_real_time_mode	memory utilization	-0.08	[-0.13, -0.03]
➖	otel_to_otel_logs	ingress throughput	-0.12	[-0.54, +0.31]
➖	process_agent_standard_check_with_stats	memory utilization	-0.26	[-0.30, -0.21]
➖	idle	memory utilization	-0.49	[-0.54, -0.43]
➖	process_agent_standard_check	memory utilization	-0.51	[-0.55, -0.47]
➖	tcp_syslog_to_blackhole	ingress throughput	-0.82	[-0.92, -0.73]
➖	file_to_blackhole	% cpu utilization	-3.29	[-10.05, +3.47]

Explanation

A regression test is an A/B test of target performance in a repeatable rig, where "performance" is measured as "comparison variant minus baseline variant" for an optimization goal (e.g., ingress throughput). Due to intrinsic variability in measuring that goal, we can only estimate its mean value for each experiment; we report uncertainty in that value as a 90.00% confidence interval denoted "Δ mean % CI".

For each experiment, we decide whether a change in performance is a "regression" -- a change worth investigating further -- if all of the following criteria are true:

1. Its estimated |Δ mean %| ≥ 5.00%, indicating the change is big enough to merit a closer look.

2. Its 90.00% confidence interval "Δ mean % CI" does not contain zero, indicating that if our statistical model is accurate, there is at least a 90.00% chance there is a difference in performance between baseline and comparison variants.

3. Its configuration does not mark it "erratic".

[chouetz]

/merge

[dd-devflow[bot]]

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